• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.433-446
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• 2021

In this study, the future flood inundation changes under a climate change were simulated in the Tonle Sap basin in Cambodia, one of the countries with high vulnerability to climate change. For the flood inundation simulation using the rainfall-runoff-inundation (RRI) model, globally available geological data (digital elevation model [DEM]; hydrological data and maps based on Shuttle elevation derivatives [HydroSHED]; land cover: Global land cover facility-moderate resolution imaging spectroradiometer [GLCF-MODIS]), rainfall data (Asian precipitation-highly-resolved observational data integration towards evaluation [APHRODITE]), climate change scenario (HadGEM3-RA), and observational water level (Kratie, Koh Khel, Neak Luong st.) were constructed. The future runoff from the Kratie station, the upper boundary condition of the RRI model, was constructed to be predicted using the long short-term memory (LSTM) model. Based on the results predicted by the LSTM model, a total of 4 cases were selected (representative concentration pathway [RCP] 4.5: 2035, 2075; RCP 8.5: 2051, 2072) with the largest annual average runoff by period and scenario. The results of the analysis of the future flood inundation in the Tonle Sap basin were compared with the results of previous studies. Unlike in the past, when the change in the depth of inundation changed to a range of about 1 to 10 meters during the 1997 - 2005 period, it occurred in a range of about 5 to 9 meters during the future period. The results show that in the future RCP 4.5 and 8.5 scenarios, the variability of discharge is reduced compared to the past and that climate change could change the runoff patterns of the Tonle Sap basin.

• Journal of Soil and Groundwater Environment
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• v.25 no.4
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• pp.14-27
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• 2020

The drought has occurred from the past, and has caused a lot of damage. It is important to analyze the past droughts and predict them in the future. In this study, the temperature and precipitation of the past and the future from climate change RCP 4.5 and 8.5 scenarios were analyzed for Seosan and Boryeong in the western region of Chungnam Province, which is considered as a drought-prone area on the Korean Peninsula. Comparing Standardized Precipitation Index (SPI) and Effective Drought Index (EDI) based on the past droughts, EDI was verified to be more suitable for the drought assessment. According to RCP 4.5, the frequency and intensity of droughts in the early future (2021~2060) were expected to increase and to be stronger. Particularly, severe droughts were predicted for a long time from 2022 to 2026, and from 2032 to 2039. Droughts were expected to decrease in the late future (2061~2100). From RCP 8.5, drought occurrences were predicted to increase, but the intensity of the droughts were expected to decrease in the future. As a result of evaluation of the frequencies of droughts by seasons, the region would be most affected by fall drought in the early future and by spring drought in the late future according to RCP 4.5. In the case of RCP 8.5, the seasonal effects were not clearly distinguished. These results suggest that droughts in the future do not have any tendency, but continue to occurr as in the past. Therefore, the measures and efforts to secure water resources and reinforcement of water supply facilities should be prepared to cope with droughts.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.130-130
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• 2022

기후변화로 인한 기상이변 현상으로 폭우와 홍수 등 수문학적 극치 사상의 출현 빈도가 잦아지고 있다. 따라서 이러한 기상이변 현상에 적응하기 위하여 보다 정확한 확률강우량 측정의 필요성이 증가하고 있다. 대장 지점의 미래 확률강우량 계산을 위해선 기후변화 시나리오의 비정상성을 고려해야 한다. 본 연구는 비정상적인 미래 기후에서 확률강우량이 어떻게 변화하는지 측정하는 것을 목표로 한다. Representative Concentration Pathway (RCP4.5)에 따른 우리나라의 확률강우량 계산에 인공신경망을 포함한 정상성, 비정상성 확률강우량 산정 모델들이 사용되었다. 지점빈도해석(AFA), 홍수지수법(IFM), 모분포홍수지수법(PIF), 인공신경망을 이용한 Quantile & Parameter regression technique(QRT & PRT)이 정상성 자료에 대해 확률강우량을 계산하는 모델로 사용되었으며, 비정상성 자료에 대해서는 비정상성 지점빈도해석(NS-AFA), 비정상성 홍수지수법(NS-IFM), 비정상성 모분포홍수지수법(NS-PIF), 인공신경망을 사용한 비정상성 Quantile & Parameter regression technique(NS-QRT & NS-PRT)이 사용되었다. Rescaled Akaike information criterion(rAIC)를 사용한 불확실성 분석과 적합도 검정을 통해서 generalized extreme value(GEV) 분포형 모델이 정상성 및 비정상성 확률강우량 산정에 가장 적합한 모델로 선정되었다. 이후, 관측자료가 GEV(0,0,0)을 따르고 시나리오 자료가 GEV(1,0,0)을 따르는 지점들을 선택하여 미래의 확률강우량 변화를 추정하였다. 각 빈도해석 모델들은 몬테카를로 시뮬레이션을 통해 bias, relative bias(Rbias), root mean square error(RMSE), relative root mean square error(RRMSE)를 바탕으로 측정하여 정확도를 계산하였으며 그 결과 QRT와 NS-QRT가 각각 정상성과 비정상성 자료로부터 가장 정확하게 확률강우량을 계산하였다. 본 연구를 통해 향후 기후변화의 영향으로 확률강우량이 증가할 것으로 예상되며, 비정상성을 고려한 빈도분석 또한 필요함을 제안하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.44-44
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• 2020

최근 기후변화의 기온 상승 및 강수량 증가의 영향으로 농업용수 수요량이 증가하고 있다. 이에 따라 농업용수의 약 60%를 공급하는 농업용 저수지의 용수 수요의 변화와 그에 따른 공급능력에 대한 평가가 필수적이다(한국농어촌공사, 2019). 본 연구에서는 기후변화 시나리오를 기반으로 농업용저수지 물수지 모의 프로그램인 DIROM(Daily Irrigation Reservoir Operation Model) 모형을 활용하여 우리나라 미래 필요수량 변화에 따른 농어촌용수 수요 변화를 분석하고, 가뭄대책단계별 관리수위를 활용해 공급능력을 평가하고자 한다. 필요수량 분석을 위해 2018년 농업생산 기반시설 통계연보의 논면적 자료 및 농어촌용수 이용 합리화계획(2015~2024)의 수로손실, 삼투량 자료를 구축하였고, 공급능력 평가를 위해 한국농어촌공사 관할 3,666개 저수지 중 저수지 시설규모, 수혜면적 등을 고려하여 선정한 426개 저수지를 대상으로 농업기반시설관리시스템(RIMS)의 저수지 제원, 내용적 곡선 및 평년저수율 자료를 수집하였다. 기후변화 시나리오는 기상청으로부터 제공받은 HadGEM3-RA RCP(Representative Concentration Pathway) 8.5 시나리오를 이용하였으며 기후변화 시나리오 기간을 S1(2021-2040), S2(2041-2070), S3(2071-2099)로 구분하여 분석하였다. 전국 필요수량을 산정한 결과 평년(1981-2005) 대비 S1, S2, S3에서 각각 12.0%, 9.1% 16.4 % 증가하여 미래로 갈수록 증가하는 경향이 나타났다. 426개 저수지에 대한 물수지 분석을 통해 저수율을 산정하고 평년저수율을 통해 산정한 가뭄대책단계별 관리수위를 기준으로 용수공급능력을 파악한 결과 저수율이 40% 미만 일이 평년대비 S1, S2, S3에서 15.9일, 11.8일, 18.1일로 증가하였다. 본 연구의 결과는 미래 기후변화에 따른 농업용 저수지 용수관리계획 및 의사결정 자료로 활용 될 것이라 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.66-66
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• 2020

최근 기후변화로 인한 전 세계적인 기온상승이 야기되고 있으며, 농업에 직접적인 영향을 주는 기상학적 및 수문학적 변화가 급격하게 진행되고 있다. 우리나라의 경우 최근 7년 동안 지역별로 극심한 가뭄이 매년 발생하고 있고, 가뭄의 발생 빈도와 강도가 증가하는 추세이다. 특히 밭의 경우 농업용 저수지 등 수리시설물로부터 관개용수를 공급받는 논 작물과 달리 자연 강우를 통해 필요한 용수량을 공급받는 천수답이 대부분이고 관개시설이 부족하기 때문에, 기후변화에 의한 가뭄의 취약성이 높다. 밭작물은 작물의 생육 시기와 기후 환경, 수자원 환경에 민감하고 토양수분을 흡수함으로써 생육하기 때문에 이러한 밭작물의 소비수량 및 관개용수량은 증발산량 뿐만 아니라 토양내 수분의 이동을 고려하여 수분 부족량을 산정해야 한다. 본 연구에서는 미래 기후변화에 의한 밭가뭄 평가를 위하여 밭 작물별 소비수량 및 관개용수량을 추정하기 위한 밭 토양수분 물수지 모형 (Soil Moisture Model)을 구성하였다. 또한 대표농도경로 (Representative Concentration Pathway, RCP) 시나리오 기반의 제5차 결합기후모델상호비교사업 (Coupled Model Intercomparison Project Phase 5, CMIP5)에서 제공하는 RCP 시나리오를 기반으로 한 전지구 기후모델 (General Circulation Model, GCM)의 기후예측결과를 적용함으로써 미래 밭 가뭄 평가를 수행하였다. 과거 기상자료 및 미래 대표농도경로 시나리오와 작물 기초자료를 수집하여 과거 및 미래 작물증발산량을 산정하였으며, 토양수분 물수지 모형에 적용하여 밭작물의 토양수분 변화를 모의하고 기후변화에 따른 작물별/생육시기별 소비수량 및 관개용수량을 추정하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.116-116
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• 2020

Gilgit-Baltistan (GB) is a highly mountainous and remote region covering 45% of Upper Indus Basin (UIB) with around 1.8 million population is vulnerable to climate change and socio-economic growth makes water resources management and planning more complex. To understand the water scarcity in the region this study is carried out to project water supply and demand for agricultural and domestic sector under various climate-socio-economic scenarios in five sub catchments of GB i.e., Astore, Gilgit, Hunza, Shigar and Shyok for a period of 2015 to 2050 using Water Evaluation and Planning (WEAP) model. For climate change scenario ensembled mean of three global climate models (GCMs) was used under three different Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP6.0 and RCP8.5). The Shared Socioeconomic Pathways (SSPs) and agricultural Land Development (LD) scenarios were combined with climate scenarios to develop climate-socio-economic scenario. Our results indicate that the climate change and socio-economic growth would create a gap between supply and demand of water in the region, with socio-economic growth (e.g. agricultural and population) as dominant external factor that would reduce food production and increase poverty level in the region. Among five catchments only Astore and Gilgit will face shortfall of water while Shyoke would face shortfall of water only under agricultural growth scenarios. We also observed that the shortfall of water in response to climate-socio-economic scenarios is totally different over two water deficient catchments due to its demography and geography. Finally, to help policy makers in developing regional water resources and management policies we classified five sub catchments of UIB according to its water deficiency level.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.567-577
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• 2015

Climate and land use changes have impact on availability water resource by hydrologic cycle change. The purpose of this study is to evaluate the hydrologic behavior by the future potential climate and land use changes in Anseongcheon watershed ($371.1km^2$) using SWAT model. For climate change scenario, the HadGEM-RA (the Hadley Centre Global Environment Model version 3-Regional Atmosphere model) RCP (Representative Concentration Pathway) 4.5 and 8.5 emission scenarios from Korea Meteorological Administration (KMA) were used. The mean temperature increased up to $4.2^{\circ}C$ and the precipitation showed maximum 21.2% increase for 2080s RCP 8.5 scenario comparing with the baseline (1990-2010). For the land use change scenario, the Conservation of Land Use its Effects at Small regional extent (CLUE-s) model was applied for 3 scenarios (logarithmic, linear, exponential) according to urban growth. The 2100 urban area of the watershed was predicted by 9.4%, 20.7%, and 35% respectively for each scenario. As the climate change impact, the evapotranspiration (ET) and streamflow (ST) showed maximum change of 20.6% in 2080s RCP 8.5 and 25.7% in 2080s RCP 4.5 respectively. As the land use change impact, the ET and ST showed maximum change of 3.7% in 2080s logarithmic and 2.9% in 2080s linear urban growth respectively. By the both climate and land use change impacts, the ET and ST changed 19.2% in 2040s RCP 8.5 and exponential scenarios and 36.1% in 2080s RCP 4.5 and linear scenarios respectively. The results of the research are expected to understand the changing water resources of watershed quantitatively by hydrological environment condition change in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.35-44
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• 2015

Forests contain a huge amount of carbon (C) and climate change could affect forest C dynamics. This study was conducted to predict the C dynamics of Pinus densiflora and Quercus variabilis forests, which are the most dominant needleleaf and broadleaf forests in Korea, using the Korean Forest Soil Carbon (KFSC) model under the two climate change scenarios (2012-2100; Constant Temperature (CT) scenario and Representative Concentration Pathway (RCP) 8.5 scenario). To construct simulation unit, the forest land areas for those two species in the 5th National Forest Inventory (NFI) data were sorted by administrative district and stand age class. The C pools were initialized at 2012, and any disturbance was not considered during the simulation period. Although the forest C stocks of two species generally increased over time, the forest C stocks under the RCP 8.5 scenario were less than those stocks under the CT scenario. The C stocks of P. densiflora forests increased from 260.4 Tg C in 2012 to 395.3 (CT scenario) or 384.1 Tg C (RCP 8.5 scenario) in 2100. For Q. variabilis forests, the C stocks increased from 124.4 Tg C in 2012 to 219.5 (CT scenario) or 204.7 (RCP 8.5 scenario) Tg C in 2100. Compared to 5th NFI data, the initial value of C stocks in dead organic matter C pools seemed valid. Accordingly, the annual C sequestration rates of the two species over the simulation period under the RCP 8.5 scenario (65.8 and $164.2g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis) were lower than those values under the CT scenario (71.1 and $193.5g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis). We concluded that the C sequestration potential of P. densiflora and Q. variabilis forests could be decreased by climate change. Although there were uncertainties from parameters and model structure, this study could contribute to elucidating the C dynamics of South Korean forests in future.

• Spatial Information Research
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• v.22 no.4
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• pp.49-58
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• 2014

Natural disasters of large scale such as typhoon, heat waves and snow storm have recently been increased because of climate change according to global warming which is most likely caused by greenhouse gas in the atmosphere. Increase of greenhouse gases concentration has caused the augmentation of earth's surface temperature, which raised the frequency of incidences of extreme weather in northern hemisphere. In this paper, we present spatial analysis of future typhoon genesis based on IPCC AR5 RCP 8.5 scenario, which applied latest carbon dioxide concentration trend. For this analysis, we firstly calculated GPI using RCP 8.5 monthly data during 1982~2100. By spatially comparing the monthly averaged GPIs and typhoon genesis locations of 1982~2010, a probability density distribution(PDF) of the typhoon genesis was estimated. Then, we defined 0.05GPI, 0.1GPI and 0.15GPI based on the GPI ranges which are corresponding to probability densities of 0.05, 0.1 and 0.15, respectively. Based on the PDF-related GPIs, spatial distributions of probability on the typhoon genesis were estimated for the periods of 1982~2010, 2011~2040, 2041~2070 and 2071~2100. Also, we analyzed area density using historical genesis points and spatial distributions. As the results, Philippines' east area corresponding to region of latitude $10^{\circ}{\sim}20^{\circ}$ shows high typhoon genesis probability in future. Using this result, we expect to estimate the potential region of typhoon genesis in the future and to develop the genesis model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.175-185
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• 2023

As drought risk increases due to climate change, various research works are underway around the world to respond to drought so as to minimize drought damage. In particular, in recent years, many studies are focused on analyzing regional patterns of drought in a comprehensive manner, however there is still insufficient to quantitatively identify drought-risk areas in a large river basin considering climate change in Korea. In this study, we calculated the Standardized Precipitation Index (SPI) and the Modified Standardized Precipitation Index (M_SPI) as representative meteorological drought index, and performed spatial autocorrelation analysis to identify the drought hotspot region under climate change scenarios of Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. The SPI was calculated by estimating parameters for each observation station within the study area, whereas the M_SPI was calculated by estimating parameters for the entire study area. It is more reasonable to use the M_SPI for assessing meteorological drought from an overall perspective within the study area. When the M_SPI was used, long-term droughts showed drought hotspot areas clearly larger than short-term droughts. In addition, the drought hotspot area moved from the center of the Nakdong River basin to the Seomjin River basin over time. Especially, the moving patterns of the short-term/long-term drought were apparent under the RCP 4.5, whereas the moving patterns of the long-term drought were distinct under the RCP 8.5 scenarios.